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| margin-based transfer learning | |
| Su Bai; Xu Wei; Shen Yidong | |
| 2009 | |
| Conference Name | 6th International Symposium on Neural Networks |
| Conference Date | 2009 |
| Conference Place | Wuhan, PEOPLES R CHINA |
| Publish Place | HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY |
| Publisher | SIXTH INTERNATIONAL SYMPOSIUM ON NEURAL NETWORKS (ISNN 2009) |
| ISSN | 1867-5662 |
| ISBN | 978-3-642-01215-0 |
| Department | Su, Bai; Shen, Yidong Chinese Acad Sci, Inst Software, State Key Lab Comp Sci, Beijing 100864, Peoples R China. |
| English Abstract | To achieve good generalization in supervised learning, the training and testing examples are usually required to be drawn from the same source distribution. However, in many cases, this identical distribution assumption might be violated when a task from one new domain(target domain) comes, while there are only labeled data from a similar old domain (auxiliary domain). Labeling the new data can be costly and it would also be a waste to throw away all the old data. In this paper, we present a discriminative approach that utilizes the intrinsic geometry of input patterns revealed by unlabeled data points and derive a maximum-margin formulation of unsupervised transfer learning. Two alternative solutions are proposed to solve the problem. Experimental results on many real data sets demonstrate the effectiveness and the potential of the proposed methods. |
| Sponsorship | Huazhong Univ Sci & Technol, Chinese Univ Hong Kong, Natl Nat Sci Fdn China, IEEE Wuhan Sect, IEEE Computat Intelligence Soc, Int Neural Network Soc, Asia Pacific Neural Network Assembly, Euorpean Neural Network Soc, Hubei Province, Syst Engn Soc, IEEE Hong Kong Joint Chapter Robot & Automat & Control Syst |
| Content Type | 会议论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/8322 |
| Collection | 基础软件与系统重点实验室 |
| Recommended Citation GB/T 7714 | Su Bai,Xu Wei,Shen Yidong. margin-based transfer learning[C]. HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY:SIXTH INTERNATIONAL SYMPOSIUM ON NEURAL NETWORKS (ISNN 2009),2009. |
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